Simultaneous detection of viable Salmonella spp., Escherichia coli, and Staphylococcus aureus in bird's nest, donkey‐hide gelatin, and wolfberry using PMA with multiplex real‐time quantitative PCR

Abstract Salmonella spp., Escherichia coli, and Staphylococcus aureus are common microbial contaminants within the homology of medicine and food that can cause serious food poisoning. This study describes a highly efficient, sensitive, specific, and simple multiplex real‐time quantitative PCR (mRT‐qPCR) method for the simultaneous detection of viable Salmonella spp., E. coli, and S. aureus. Primers and probes were designed for the amplification of the target genes invA, uidA, and nuc. Dead bacterial genetic material was excluded by propidium monoazide (PMA) treatment, facilitating the detection of only viable bacteria. This method was capable of detecting Salmonella spp., E. coli, and S. aureus at 102, 102, and 101 CFU/ml, respectively, in pure culture. PMA combined with mRT‐qPCR can reliably distinguish between dead and viable bacteria with recovery rates from 95.7% to 105.6%. This PMA‐mRT‐qPCR technique is a highly sensitive and specific method for the simultaneous detection of three pathogens within the homology of medicine and food.

poisoning. Salmonella spp., Escherichia coli, and Staphylococcus aureus are common pathogenic microorganisms responsible for food poisoning (Elmonir et al., 2021;Kareem & Al-Ezee, 2020;Soon et al., 2020;Wang et al., 2017). In China, the National Food Safety Standards clearly stipulate acceptable limits for these bacteria and the Chinese Pharmacopoeia defines the relevant regulations.
Salmonella spp. are the most harmful and must not be detectable.
Thus, there is an urgent need to establish a simple, rapid, sensitive, specific, and simultaneous detection method for these three bacteria to diminish the dilemma.
The commonly used method for the detection of pathogenic bacteria is the conventional culture method that identifies targeted bacteria based on whether they can be cultured.
However, culturing is complicated and time-consuming (Kawasaki et al., 2003). Moreover, food samples may contain bacteria that cause competitive inhibition, or dormant or metabolically abnormal bacteria that cannot be successfully cultured, raising the possibility of missed detections and false-negative results.
Molecular biology techniques such as polymerase chain reaction (PCR)-based methods have been widely used in the detection of pathogenic bacteria. These are simple, rapid, low-cost, and multifunctional (Xie et al., 2020;Zhang et al., 2018;Zhu et al., 2018).
PCR technology includes PCR (Schochetman et al., 1988), fluorescent quantitative PCR (qPCR; Simonetti et al., 1992), and digital PCR (dPCR; Vogelstein & Kinzler, 1999). qPCR monitors the entire reaction process through changes in the intensity of fluorescent signals, enabling real-time detection and quantification of the cycle threshold (Ct) via a standard curve .
The specificity of the TaqMan probe method is higher than the SYBR Green dye method and is capable of multiplex detection via the design of different fluorescent probes (Nejati et al., 2020;Zhang et al., 2015). However, the conventional PCR method cannot distinguish between viable and dead bacteria, which can cause interference leading to false-positive results (Kim et al., 2015). A novel technique to detect viable bacteria combined PCR with a nucleic acid cross-linking dye (Nogva et al., 2003). Elimination of the false positives caused by dead cells has been achieved by combining propidium monoazide (PMA) pretreatment with qPCR (Chen et al., 2011). PMA is a nucleic acid cross-linking agent that selectively enters dead bacteria and binds to genomic DNA, thereby preventing its amplification during PCR. The azido group in any excess PMA reacts with water to produce hydroxylamine, inactivating the PMA (Liang et al., 2019).
In this study, PMA and mRT-qPCR were combined to simultaneously detect and quantify viable Salmonella spp., E. coli, and S. aureus.
Three pairs of primers and probes were designed for the multiplex detection of the target bacteria based on specific genes. Multiplex fluorescent probes were employed in this PMA-pretreatment qPCR assay for the simultaneous detection of viable bacteria. The applicability of the method was assessed in bird's nest, donkey hide gelatin, and wolfberry samples.

| Bacterial strains and culture conditions
The bacterial strains used in this study, including seven target bacteria and four non-target bacteria, are listed in Table 1. The strains were resuscitated in nutrient agar and cultured in brain-heart infusion at 37℃ (Beijing Land Bridge Technology Ltd.). Suspensions of dead Salmonella spp., E. coli, and S. aureus were obtained by heat treating in a metal bath at 80℃ for 10 min, followed by in ice water for 5 min, followed by plate coating to determine that there were only dead bacteria.

| Bacterial strains genomic DNA extraction
A simple and rapid boiling method was used to extract bacterial genomic DNA. Pure bacterial culture broth (1 ml) was centrifuged at 12,000 g for 3 min, the supernatant discarded, and PBS buffer (0.01 M, pH 7.4) added to resuscitate the cells. This operation was repeated, and the cells suspended in 100 μl ultra-pure water. This suspension was boiled for 10 min, placed in an ice water bath for 5 min, centrifuged at 12,000 g for 3 min, and the supernatant containing the bacterial genomic DNA was stored at −20°C.

No.
Bacterial strains Source

| Design of primers and probes
Primer Premier 5.0 and Beacon Designer 8 software were used to design specific primers and probes, respectively, based on the genus-specific gene invA (Salmonella spp.; Bülte & Jakob, 1995), the species-specific gene uidA (E. coli; Kibbee et al., 2013), and the species-specific gene nuc (S. aureus; Kim et al., 2001). All primers and probes were determined to be specific by BLAST analysis (National Center for Biotechnology Information). Primers and probes were synthesized by Sangon Biotech (Shanghai, China) to HPLC purification grade. All qPCR processes were performed on a Bio-Rad CFX96 Touch System. Oligonucleotide sequences of primers and probes are listed in Table 2.

TA B L E 2 Primers and probe sequence used in this study
S C H E M E 1 Schematic illustration of PMA-mRT-qPCR for simultaneous detection of Salmonella spp., Escherichia coli, and Staphylococcus aureus annealing and extension. The annealing temperature was optimized by gradient qPCR and temperature range was set as 55-65°C.

| mRT-qPCR standard curve and limit of detection (LOD)
The target bacteria were cultured overnight, subjected to PMA treatment, and their genomic DNA was extracted and diluted in a 10-fold gradient (10 8 -10 1 CFU/ml). Genomic DNA in pure culture medium was analyzed by both simplex and multiplex qPCR. Standard curves were established, correlating Ct values against bacterial concentrations.
To verify the applicability of the PMA-mRT-qPCR assay, artificially contaminated common food samples (donkey hide gelatin, bird's nest, and wolfberry) were analyzed. These were purchased from a local drugstore (Drugstore) and 1 g of each food was homogenized with 9 ml PBS. The absence of the three target pathogens was confirmed by culturing. The homogenates were inoculated with Salmonella spp., E. coli, and S. aureus at 10 1 to 10 7 CFU/ml and suspended in 100 μl ultra-pure water after being treated with PMA.
Simplex and multiplex qPCR reactions were optimized for the detection of viable cells in these artificially contaminated samples. All assays were conducted in triplicate in line with Scheme 1 which illustrates the principle and process of PMA-mRT-qPCR detection.

| Recovery rate
To determine the accuracy of the method, mixed bacterial suspensions containing known numbers of dead and viable bacteria were prepared: 10 8 , 10 6 , 10 4 , and 10 0 CFU/ml dead bacteria (determined by culture) and 10 7 CFU/ml viable bacteria. Duplicate groups were treated with PMA and DNA was extracted for mRT-qPCR determination. Ct values were used for the evaluation of recovery.

| Data analysis
All data are expressed as mean ± standard deviation. Data from op-

| Optimization of PMA-mRT-qPCR
Primers and probes were designed according to specific genes in the three target pathogenic bacteria and fluorescent groups were modified to achieve simultaneous multiplex detection. As shown in Figure 1, mRT-qPCR produced three different amplification curves and strong fluorescence signals, indicating that the primers and probes could amplify the target genes simultaneously and accurately.
The annealing temperature during mRT-qPCR amplification was optimized. As shown in Figure

| Simplex and multiplex PMA-qPCR performance
Simplex PMA-qPCR was used to evaluate the performance of the method for detecting each species. Figure 4a is the standard curve Standard curves were also established using the optimized PMA-mRT-qPCR multiplex assay. Linear correlation was R 2 = .9975 for Salmonella spp., R 2 = .9984 for E. coli, and R 2 = .9972 for S. aureus ( Figure 5). The LODs were 10 2 CFU/ml for Salmonella spp. and E. coli, and 10 1 CFU/ml for S. aureus. The PMA-mRT-qPCR established in this study can simultaneously detect three pathogenic bacteria, and the detection sensitivity was greatly improved compared with previous studies (Forghani et al., 2016), indicating that the primers and probes have great practical application potential.

| Evaluation of practical applications
The applicability of this novel PMA-mRT-qPCR assay in samples relevant to the homology of medicine and food was demonstrated using artificially inoculated donkey hide gelatin, bird's nest, and wolfberry.
Standard curves were established using simplex and multiplex qPCR for each food type. As shown in Figure 6, the linearity and sensitivity of simplex qPCR of Salmonella spp. were R 2 = .9994 and LOD 10 2 CFU/ml for donkey hide gelatin, R 2 = .9957 and LOD 10 2 CFU/ml for bird's nest, and R 2 = .9971, and LOD 10 4 CFU/ml for wolfberry.
Simplex qPCR of S. aureus produced R 2 = .9992 and LOD 10 2 CFU/ ml for donkey hide gelatin, R 2 = .9993 and LOD 10 3 CFU/ml for bird's nest, and R 2 = .9979 and LOD 10 5 CFU/ml for wolfberry ( Figure 8). Figure 9 shows the multiplex qPCR standard curves and LODs of the three target bacteria in various food types. All three standard curves exhibited good linear correlations and ranges in donkey hide gelatin (Figure 9a). Detection sensitivity was 10 2 CFU/ml for Salmonella spp. and E. coli, and 10 3 CFU/ml for S. aureus. Figure 9b shows that Salmonella spp. and E. coli had good linear ranges in bird's nest, while the S. aureus range was narrower. Multiplex LODs were determined to be 10 2 CFU/ml for Salmonella spp., 10 3 CFU/ml for

| Method selectivity
Selectivity of the PMA-mRT-qPCR method was assessed by testing 11 bacterial strains, including seven target bacteria (Table 1).
Amplification results showed that the invA gene can be used to specifically detect strains of Salmonella spp., the uidA gene can be used to detect strains of E. coli, and the nuc gene can be used to detect strains of S. aureus. The results show that the target genes selected in this study have good selectivity, and similar results were found for in previous studies (Baron et al., 2004;Liu et al., 2018;Yanestria et al., 2019).

| CON CLUS ION
A rapid, simple, and sensitive method combining PMA and mRT-qPCR has been developed for the simultaneous detection of viable Salmonella spp., E. coli, and S. aureus in sample types within the homology of medicine and food. Three specific primers and probes were designed for multiplex qPCR amplification to detect the target bacteria. The optimized assay could specifically detect 10 2 CFU/ml of Salmonella spp., 10 2 CFU/ml of E. coli, and 10 1 CFU/ml of S. aureus in a pure medium. Detection sensitivity differed in various food substrates (bird's nest, donkey hide gelatin, and wolfberry). This method can be used for the safety monitoring of micro-organisms in medicines and foods, particularly when the abundance of bacteria is limited. for financial support.

CO N FLI C T S O F I NTE R E S T
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

DATA AVA I L A B I L I T Y S TAT E M E N T
Research data are not shared.